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EconData

by Codera Analytics · Since 2016
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ActiveAvailable globallyCloud
Quick facts
VendorCodera Analytics
Year launched2016
StatusActive
LocationCape Town, South Africa.
Countries servedGlobal
Languages1
Integrations1+
Free tierN/A
Free trialN/A
Contact salesYES

About EconData

EconData is an econometric data services platform from Codera Analytics that enables automation of analytical workflows that depend on public domain or third-party data. It combines African economic and financial data, automatable data, and automatable workflows so users can effectively manage complex analyses. The platform is designed to facilitate data-driven decision-making by allowing analysts to automate repetitive tasks and focus on strategic activities. EconData supports importing data from various sources, customizing analytical models, and generating forecasts that are essential for research and business planning. Key capabilities: African economic data automatable workflows data integration customizable models forecasting tools Best for: analysts and researchers that need efficient processing of economic and financial data.

EconData is a leading provider of time‑series data management software and econometric data services, offering tools that help analysts, economists, financial institutions, and government agencies manage, manipulate, and automate large collections of time‑series datasets. According to the official EconData website, the company’s flagship product dXtime represents over 20 years of development in time‑series software, delivering fast, intuitive access even when working with extremely large datasets. EconData.com (dX Software & dX Databases) is a branch that focuses on time‑series data management, offering the dXtime desktop application and subscription‑based dX databases. These databases give users access to large, frequently updated economic and financial datasets in a proprietary dX format. EconData.co.za (Econometric Data Services) is a platform that provides African economic and financial data, enabling automation of analytical workflows, model governance, and forecast management. It supports data‑sharing, model automation, historical vintages, and multi‑format downloads, with integrations for R and Python packages. The platform also offers an Excel Add‑In, allowing users to pull time‑series data directly into spreadsheets for modeling, charting, and updating quantitative workflows.

Pros & Cons

Pros
  • Centralizes economic time series data for easier access and research
  • Helps automate data workflows using Excel R or Python packages
  • Supports historic vintages and updatable series for forecasting workflows
  • Integrates public domain and proprietary data into unified datasets
  • Makes complex macroeconomic datasets easier to query and analyze
Cons
  • Requires subscription for premium or larger datasets for commercial use
  • Best value requires some coding skill in R Python or Excel add-ins
  • Not optimized for non-economic data use cases or general analytics
  • Initial learning to query and automate data may take time
  • Data coverage varies by module and available series

Features

Key features

High‑performance time‑series engine – Manages massive datasets efficiently using optimized data‑processing and retrieval algorithms.
dXtime desktop application – Provides intuitive tools for manipulating and analyzing time‑series information.
20‑year software lineage – Delivers mature, stable functionality refined through decades of development experience.
Subscription‑based dX databases – Supplies continuously updated economic datasets in proprietary structured formats.
Fast data access tools – Retrieves large time‑series collections quickly for real‑time analysis workflows.
Econometric workflow automation – Streamlines repetitive modeling tasks through automated data pipelines.
Forecast‑management system – Supports scenario tracking, model governance, and historical vintage comparisons.
Cross‑database data sharing – Enables seamless movement of datasets across institutional repositories.
User‑level access control – Manages permissions for analysts, teams, and organizational departments.
Historical data vintages – Preserves past dataset versions for accurate model evaluation.

Additional features

R package integration – Automates data downloads directly into R‑based analytical environments.
Python package support – Enables scripted data ingestion for machine‑learning workflows.
Excel Add‑In functionality – Pulls time‑series data directly into spreadsheet models.
Automated dataset updates – Refreshes data sources without manual intervention or re‑downloads.
Multi‑format data export – Outputs datasets into formats suitable for modeling and reporting.
Model‑governance framework – Ensures transparency and reproducibility across forecasting processes.
Secure data‑sharing tools – Protects sensitive economic information within institutional boundaries.
Econometric modeling support – Facilitates regression, forecasting, and statistical analysis workflows.
Large‑dataset compatibility – Handles extensive economic databases without performance degradation.
Public‑domain data ingestion – Integrates external sources into unified analytical environments.

Pricing

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Countries & Languages

Global
Countries served
1
Interface languages
1
Billing currencies

Interface languages

English

Billing currencies

RAN

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